Category Archives: Definitions

Day_57 : Normalcy Bias

We tend not to admit unusual situation. This is the crucial point for disaster risk reduction. In Japan, there are so many true stories about the bias as follows:

So many victims told me “I thought I was ok, that thing (Fooding) would never happen to me, ” even if their neighbors were already affected.                                         – Researchers Note-

The very insightful information was found from the following site:
https://geroldblog.com/2013/04/26/beware-your-dangerous-normalcy-bias/

The followings are from the above Gerold Blog:
C) When Mount St. Helens volcano began rumbling in Washington State in 1980, Park Rangers issued warnings for resident to leave and blocked access to keep people out. Some residents ignored evacuation warnings and other campers and sightseers walked or drove around the barricades to get into the park. They’d always camped there and since there had never been a disaster before; their normalcy bias prevented them from understanding the possibility of one happening. Then the volcano violently erupted and 57 people were killed.

D) Before Hurricane Katrina hit New Orleans in 2005, inadequate preparation by both governments and citizens as well as constant denials that the levees could fail are an example of normalcy bias as were the thousands of people who refused to evacuate. After the hurricane, many of the Louisiana Super dome refugees were unable to cope with the disaster. Many people couldn’t understand that a hurricane could devastate their city and, unable to help themselves, they waited in vain for government help that never came as murders and rapes escalated, sewers backed up, and food and water ran out. Normalcy bias left them unable to deal with the disaster.”

Day_49 : CRED disaster definition

Centre for Research on Epidemiology of Disasters (CRED)’s EM-DAT is the basic database to do disaster research.We can refer how they count the disasters.

CRED Disaster definition:
1.10 or more people reported killed
2.100 people reported affected
3.Declaration of a state of emergency
4.Call for international assistance

More than one of those are confirmed, the CRED counts the event as a disaster

Ref.
http://emdat.be/explanatory-notes

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Day_31 : 人口と災害【2】[Japanese]

人口と災害について、指標研究では、社会脆弱性指標、リジリエンス指標が中心課題となっている。社会脆弱性指標については、サウスカロライナ大学のカッター*などが先駆的で大きな貢献をなしてきた。その社会脆弱性指標の延長として近年数多くの成果が出されてきているのがリジリエンス指標研究である。どちらの指標研究も基本は、Wisnerら(2004)のPressure and Release(PAR)モデルが理論的な下敷きになっており、リスクを、Risk(リスク)=H(ハザード)× V(バルナラビリティ)で考え、リスクは、ハザードとバルナラビリティの重なった部分ととらえる。ハザードには自然現象(例えば降雨量)が、バルナラビリティには社会的な条件が当てはまり、このバルナラビリティに関しては、地域の暴露人口、高齢化率、男女比、識字率、さらには所得などの統計データを用いることによって指標化が可能となる。リジリエンス指標については、教育レベルや収入等より長期的な視点を含めた変数を加えたものである。GISなどの技術の進歩とともにこれらの結果が地図上に落とし込まれ地域毎の社会的脆弱性、リジリエンス、及びリスクが可視化されるようなり、指標研究が進んだ。 これらの指標研究は、実用的な研究としても多くの防災・災害研究者が取り組んでいる。ただ、国や地域により、災害や各種統計データに格差があることや、実際の災害による妥当性の検証などの問題を常に抱えていることも確かである。これらの問題の対応として、ターゲッ地域へのフィールド調査による質的な情報を組み合わせる指標への試みもなされてきている。

*スーザン・カッター サウスカロライナ大学(米国) ハザードと脆弱性研究所教授・. 所長

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Day_29 : Human Vulnerability Index

I am developing the Human Vulnerability Index.

If you have some ideas about this issue, please let me know.

The HVI was originally developed when I was doing research on the Great East Japan Earthquake and Tsunami (GEJET) disaster in 2011. I needed to compare the disaster impact by municipality for not only the 2011 tsunami but also the 1896, 1933, and 1960 tsunamis. However, it was difficult to compare because geographical and population sizes are different by municipality. So the HVI was developed. A member of JAEE thankfully recognized this for the applications.

The following are just some parts; I will disclose the details in the paper and post the link here in the near future.

1. The HVI can be applied to compare the municipalities not only for the GEJET disaster but also with the historical tsunami events and clarify the historical trends.

2. The recurrent HVI was calculated by a ridge regression analysis using the evacuation-related factors, which this paper estimated based on some theories, such as the PAR model.

3. The HVI was also applied to two international cases: the 2004 Indian Ocean Tsunami and the 2005 Hurricane Katrina.

The HVI-related paper was published with Dr.Yozo Goto.
https://www.researchgate.net/publication/329961277_HUMAN_VULNERABILITY_INDEX_FOR_EVALUATING_TSUNAMI_EVACUATION_CAPABILITY_OF_COMMUNITIES_Eng_Version

Day_28 : サイクルモデル 【1】 [Japanese]

開発・環境・災害のサイクルモデルというのを大分前ですが、提唱させて頂きました。アブストラクトは以下です。
http://ci.nii.ac.jp/naid/110008664615
簡単にいえば、開発が環境を改変し、環境が災害を生み出すということです。開発にも、経済開発、社会開発、人間開発とあり、それぞれ、内からと外からの見方があります。環境には、自然環境と社会環境があります。災害は以前述べたように、自然災害、技術災害、そして人為的災害からなります。このサイクルモデルを今後もっと有効に使おうと考えています。

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Day_23 : The Definitions

Day 14 shows disasters can be categorized into natural, technological, and human-made disasters. Natural disasters can be considered a relationship between humans and nature. Technological disasters come from the interactions between humans and technology that people create. The conflicts between humans and humans cause human-made disasters. This idea is the basis for understanding natural disasters. The 2011 Fukushima nuclear plant issue is a technological disaster and a natural disaster, so we can call it a complex disaster. These understandings are based on what I learned before.